YOUNG PEOPLE FEEL WISE, OLD PEOPLE FEEL ENERGETIC: COMPARING AGE STEREOTYPES AND SELF-EVALUATIONS ACROSS ADULTHOOD

Using questionnaire data from the MIDUS study (N=6.325) we examined the extent to which people in their late 20s, 40s, and 60s think that positive stereotypic “old” and “young” characteristics describe themselves, their age peers, and other age groups. A constellation of “old” characteristics (e.g., wise, caring, calm) was seen as more descriptive of older adults, while a constellation of “young” characteristics (e.g., healthy, energetic) was seen as more descriptive of younger adults. Self-evaluations were highly positive and largely consistent across age groups. Compared to their age peers, younger adults saw themselves as having as many positive “young” characteristics but more positive “old” characteristics whereas older adults saw themselves as having more positive “young” characteristics but fewer positive “old” characteristics. The results support the stability of the aging self despite the existence of age stereotypes and the role of negative age stereotypes as a frame of reference for making self-evaluations

SUBJECTIVE AGING: SOMETHING UNIQUE OR JUST ANOTHER EXPRESSION OF GENERAL SELF-BELIEFS?

Using data from the German Ageing Survey (adults aged 40‒85), this study tested the convergent and discriminant validity of subjective aging measures by comparing three different measures of subjective aging with one another and relating them to established measures of general self-beliefs (optimism, self-efficacy, subjective health) and subjective well-being (depression, affect). Correlations between subjective aging measures ranged from ‒.61 (amongst general self-perceptions of aging measures) to ‒.09, with subjective age being least related to the other measures. The highest overlap was observed between optimism and global self-perceptions of aging (.69) and it was for these global self-perceptions that the highest amount of variance could be explained by correlates in a regression analysis (R-square=.55). In contrast, only 10% of variance could be explained for subjective age. Our results underline the merit of taking the multidimensional nature of subjective aging into account since global measures appear less distinct from general personality traits

Carbon and nitrogen isotopic ratios of urine and faeces as novel nutritional biomarkers of meat and fish intake

Purpose Meat and fish consumption are associated with changes in the risk of chronic diseases. Intake is mainly assessed using self-reporting, as no true quantitative nutritional biomarker is available. The measurement of plasma fatty acids, often used as an alternative, is expensive and time-consuming. As meat and fish differ in their stable isotope ratios, δ13C and δ15N have been proposed as biomarkers. However, they have never been investigated in controlled human dietary intervention studies. Objective In a short-term feeding study, we investigated the suitability of δ13C and δ15N in blood, urine and faeces as biomarkers of meat and fish intake. Methods The dietary intervention study (n = 14) followed a randomised cross-over design with three eight-day dietary periods (meat, fish and half-meat–half-fish). In addition, 4 participants completed a vegetarian control period. At the end of each period, 24-h urine, fasting venous blood and faeces were collected and their δ13C and δ15N analysed. Results There was a significant difference between diets in isotope ratios in faeces and urine samples, but not in blood samples (Kruskal–Wallis test, p < 0.0001). In pairwise comparisons, δ13C and δ15N were significantly higher in urine and faecal samples following a fish diet when compared with all other diets, and significantly lower following a vegetarian diet. There was no significant difference in isotope ratio between meat and half-meat–half-fish diets for blood, urine or faecal samples. Conclusions The results of this study show that urinary and faecal δ13C and δ15N are suitable candidate biomarkers for short-term meat and fish intake

A Statistical Method for Generating Temporally Downscaled Geochemical Tracers in Precipitation

Sampling intervals of precipitation geochemistry measurements are often coarser than those required by fine-scale hydrometeorological models. This study presents a statistical method to temporally downscale geochemical tracer signals in precipitation so that they can be used in high-resolution, tracer-enabled applications. In this method, we separated the deterministic component of the time series and the remaining daily stochastic component, which was approximated by a conditional multivariate Gaussian distribution. Specifically, statistics of the stochastic component could be explained from coarser data using a newly identified power-law decay function, which relates data aggregation intervals to changes in tracer concentration variance and correlations with precipitation amounts. These statistics were used within a copula framework to generate synthetic tracer values from the deterministic and stochastic time series components based on daily precipitation amounts. The method was evaluated at 27 sites located worldwide using daily precipitation isotope ratios, which were aggregated in time to provide low resolution testing datasets with known daily values. At each site, the downscaling method was applied on weekly, biweekly and monthly aggregated series to yield an ensemble of daily tracer realizations. Daily tracer concentrations downscaled from a biweekly series had average (+/- standard deviation) absolute errors of 1.69‰ (1.61‰) for δ2H and 0.23‰ (0.24‰) for δ18O relative to observations. The results suggest coarsely sampled precipitation tracers can be accurately downscaled to daily values. This method may be extended to other geochemical tracers in order to generate downscaled datasets needed to drive complex, fine-scale models of hydrometeorological processes

Retirement age and disability status as pathways to later-life cognitive impairment: Evidence from the Norwegian HUNT Study linked with Norwegian population registers

Background Research shows that retirement age is associated with later-life cognition but has not sufficiently distinguished between retirement pathways. We examined how retirement age was associated with later-life dementia and mild cognitive impairment (MCI) for people who retired via the disability pathway (received a disability pension prior to old-age pension eligibility) and those who retired via the standard pathway. Methods The study sample comprised 7210 participants from the Norwegian Trøndelag Health Study (HUNT4 70+, 2017–2019) who had worked for at least one year in 1967–2019, worked until age 55+, and retired before HUNT4. Dementia and MCI were clinically assessed in HUNT4 70+ when participants were aged 69–85 years. Historical data on participants' retirement age and pathway were retrieved from population registers. We used multinomial regression to assess the dementia/MCI risk for women and men retiring via the disability pathway, or early (<67 years), on-time (age 67, old-age pension eligibility) or late (age 68+) via the standard pathway. Results In our study sample, 9.5% had dementia, 35.3% had MCI, and 28.1% retired via the disability pathway. The disability retirement group had an elevated risk of dementia compared to the on-time standard retirement group (relative risk ratio [RRR]: 1.64, 95% CI 1.14–2.37 for women, 1.70, 95% CI 1.17–2.48 for men). MCI risk was lower among men who retired late versus on-time (RRR, 0.76, 95% CI 0.61–0.95). Conclusion Disability retirees should be monitored more closely, and preventive policies should be considered to minimize the dementia risk observed among this group of retirees.publishedVersio

Evaluation of formal IDEs for human-machine interface design and analysis: the case of CIRCUS and PVSio-web

Critical human-machine interfaces are present in many systems including avionics systems and medical devices. Use error is a concern in these systems both in terms of hardware panels and input devices, and the software that drives the interfaces. Guaranteeing safe usability, in terms of buttons, knobs and displays is now a key element in the overall safety of the system. New integrated development environments (IDEs) based on formal methods technologies have been developed by the research community to support the design and analysis of high-confidence human-machine interfaces. To date, little work has focused on the comparison of these particular types of formal IDEs. This paper compares and evaluates two state-of-the-art toolkits: CIRCUS, a model-based development and analysis tool based on Petri net extensions, and PVSio-web, a prototyping toolkit based on the PVS theorem proving system.This work is partially supported by: Project NORTE-01-0145-FEDER-000016, financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF); Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) PhD scholarship

Predicting forefoot-orthosis interactions in rheumatoid arthritis using computational modelling

Foot orthoses are prescribed to reduce forefoot plantar pressures and pain in people with rheumatoid arthritis. Computational modelling can assess how the orthoses affect internal tissue stresses, but previous studies have focused on a single healthy individual. This study aimed to ascertain whether simplified forefoot models would produce differing biomechanical predictions at the orthotic interface between people with rheumatoid arthritis of varying severity, and in comparison to a healthy control. The forefoot models were developed from magnetic resonance data of 13 participants with rheumatoid arthritis and one healthy individual. Measurements of bony morphology and soft tissue thickness were taken to assess deformity. These were compared to model predictions (99th% shear strain and plantar pressure, max. pressure gradient, volume of soft tissue over 10% shear strain), alongside clinical data including body mass index and Leeds Foot Impact Scale–Impairment/Footwear score (LFIS-IF). The predicted pressure and shear strain for the healthy participant fell at the lower end of the rheumatoid models’ range. Medial first metatarsal head curvature moderately correlated to all model predicted outcomes (0.529 < r < 0.574, 0.040 < p < 0.063). BMI strongly correlated to all model predictions except pressure gradients (0.600 < r < 0.652, p < 0.05). There were no apparent relationships between model predictions and instances of bursae, erosion and synovial hypertrophy or LFIS-IF score. The forefoot models produced differing biomechanical predictions between a healthy individual and participants with rheumatoid arthritis, and between individuals with rheumatoid arthritis. Models capable of predicting subject specific biomechanical orthotic interactions could be used in the future to inform more personalised devices to protect skin and soft tissue health. While the model results did not clearly correlate with all clinical measures, there was a wide range in model predictions and morphological measures across the participants. Thus, the need for assessment of foot orthoses across a population, rather than for one individual, is clear